U.S. patent application number 17/015959 was filed with the patent office on 2020-12-31 for method and apparatus for image filtering with adaptive multiplier coefficients.
The applicant listed for this patent is Huawei Technologies Co., Ltd.. Invention is credited to Jianle CHEN, Semih ESENLIK, Anand Meher KOTRA, Zhijie ZHAO.
Application Number | 20200413053 17/015959 |
Document ID | / |
Family ID | 1000005105815 |
Filed Date | 2020-12-31 |
United States Patent
Application |
20200413053 |
Kind Code |
A1 |
ESENLIK; Semih ; et
al. |
December 31, 2020 |
METHOD AND APPARATUS FOR IMAGE FILTERING WITH ADAPTIVE MULTIPLIER
COEFFICIENTS
Abstract
An apparatus and a method filters reconstructed images, in
particular, video images, with adaptive multiplicative filters. The
apparatus and method groups the multiplier coefficients of the
filter into at least two groups; determines the value of each
multiplier coefficient in a first group so as to be allowed to
assume any value in a first set of allowed values of multiplier
coefficients, determines the value of each multiplier coefficient
in a second group so as to be allowed to assume any value in a
second set of allowed values of multiplier coefficients, and
filters the set of samples of an image with the filter. At least
one of the first and second sets has at least one value that is not
in the other set.
Inventors: |
ESENLIK; Semih; (Munich,
DE) ; ZHAO; Zhijie; (Munich, DE) ; KOTRA;
Anand Meher; (Munich, DE) ; CHEN; Jianle;
(Santa Clara, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Huawei Technologies Co., Ltd. |
Shenzhen |
|
CN |
|
|
Family ID: |
1000005105815 |
Appl. No.: |
17/015959 |
Filed: |
September 9, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
PCT/EP2018/058091 |
Mar 29, 2018 |
|
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17015959 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04N 19/157 20141101;
H04N 19/463 20141101; H04N 19/82 20141101; H04N 19/117
20141101 |
International
Class: |
H04N 19/117 20060101
H04N019/117; H04N 19/82 20060101 H04N019/82; H04N 19/157 20060101
H04N019/157; H04N 19/463 20060101 H04N019/463 |
Foreign Application Data
Date |
Code |
Application Number |
Mar 9, 2018 |
EP |
PCT/EP2018/055981 |
Claims
1. An apparatus for filtering a set of samples of an image using a
filter with adaptive multiplier coefficients represented by integer
numbers, the apparatus comprising processing circuitry which is
configured to: group the multiplier coefficients of the filter into
at least two groups, comprising a first group and a second group;
determine a value of each of the multiplier coefficients in the
first group so as to be allowed to assume any value in a first set
of allowed values of multiplier coefficients, determine a value of
each of the multiplier coefficients in the second group so as to be
allowed to assume any value in a second set of allowed values of
multiplier coefficients, and filter the set of samples of the image
with the filter, wherein at least one of the first set or the
second set has at least one value that is not in the other set.
2. The apparatus according to claim 1, wherein the allowed values
of the first set are all values within a range defined by a
predetermined maximum N.sub.max of absolute values of the
multiplier coefficients.
3. The apparatus according to claim 1, wherein the allowed values
of the first set are all values that are representable by an L bit
integer plus a sign bit, wherein L is a positive integer.
4. The apparatus according to claim 2, wherein the allowed values
of the second set are all values that can be represented by a l bit
integer plus a sign bit, wherein l<ceil(log.sub.2(N.sub.max)) or
l<L.
5. The apparatus according to claim 1, wherein the allowed values
of the second set are all values within a range defined by a
predetermined maximum P.sub.max of absolute values of the
multiplier coefficients, which are divisible by a factor 2.sup.M,
wherein M is a positive integer.
6. The apparatus according to claim 1, wherein the allowed values
of the second set are restricted to values such that a binary
representation of an absolute value with a predetermined number of
digits has at least one "zero".
7. The apparatus according to claim 6, wherein the allowed values
of the second set are restricted to values such that the binary
representation of the absolute value of each of the multiplier
coefficients includes at most two "ones" or at least one "one".
8. The apparatus according to claim 1, wherein the set of samples
of an image is a set of samples of a video image.
9. The apparatus according to claim 8, wherein the apparatus is
configured to individually adapt the multiplier coefficients for
each image and each pixel.
10. A method for filtering a set of samples of an image using a
filter with adaptive multiplier coefficients represented by integer
numbers, the method comprising: grouping the multiplier
coefficients of the filter into at least two groups, comprising a
first group and a second group; determining a value of each of the
multiplier coefficients in a first group so as to be allowed to
assume any value in a first set of allowed values of multiplier
coefficients, determining a value of each of the multiplier
coefficients in a second group so as to be allowed to assume any
value in a second set of allowed values of multiplier coefficients,
and filtering the set of samples of the image with the filter,
wherein at least one of the first set or the second set has at
least one value that is not in the other set.
11. An apparatus for encoding a current set of samples of an
unencoded image including a plurality of pixels, the apparatus
comprising: an encoder with a decoder for reconstructing the
current set, and the apparatus according to claim 1 for filtering
the reconstructed set.
12. The apparatus according to claim 11, further comprising
processing circuitry, which is configured to: map the values of the
multiplier coefficients to binary code words; and include the
code_words in a bit stream for transmittal to a decoding
apparatus.
13. The apparatus according to claim 12, wherein a length of the
code_words depends on the number of distinct multiplier coefficient
values.
14. The apparatus according to claim 12, wherein the processing
circuitry is further configured to: perform a prediction of the
multiplier coefficients of the filter; and determine residual
multiplier coefficients by comparing the actually determined values
with predicted values resulting from the prediction, wherein the
mapping to the binary codewords is applied to the residual
multiplier coefficients.
15. The apparatus according to claim 14, wherein the processing
circuitry is further configured to generate prediction control
information and to include the prediction control information into
the bit stream.
16. An apparatus for decoding a coded current set of samples of an
encoded image including a plurality of pixels, the apparatus
comprising: a decoder for reconstructing the current set, and the
apparatus according to claim 1 for filtering the reconstructed
set.
17. The apparatus according to claim 16, wherein the processing
circuitry is further configured to obtain multiplier coefficients
from binary code_words included in a received bit stream by
applying a mapping operation.
18. The apparatus according to claim 17, wherein the obtained
multiplier coefficients are residual multiplier coefficients
representing a difference between actual coefficient values and
multiplier coefficients predicted according to a prediction; and
the processing circuitry is configured to determine the values of
the multiplier coefficients of the filter by reconstructing them
from the obtained residual multiplier coefficients.
19. The apparatus according to claim 18, wherein a scheme of the
prediction is indicated by prediction control information further
included in the received bit stream; and the processing circuitry
is configured to further use the prediction control information in
the reconstruction.
20. The apparatus according to claim 17, wherein the determination
by the processing circuitry further comprises: performing a
determination as to whether or not the determined values of
multiplier coefficients, obtained directly from the received bit
stream by the mapping operation or by reconstruction from the
obtained residual multiplier coefficients, are within a respective
set of allowed values; and based on determining that the determined
values of multiplier coefficients are not within the respective set
of allowed values, converting the determined value to a nearest
value that is within the respective set of allowed values.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of International
Application No. PCT/EP2018/058091, filed on Mar. 29, 2018, which
claims priority to International Application No. PCT/EP2018/055981,
filed on Mar. 9, 2018. The disclosures of the aforementioned
applications are hereby incorporated by reference in their
entireties.
FIELD
[0002] Embodiments of the present disclosure relate to the field of
picture processing, for example, video picture and/or still picture
coding.
BACKGROUND
[0003] Video coding (video encoding and decoding) is used in a wide
range of digital video applications, for example broadcast digital
TV, video transmission over internet and mobile networks, real-time
conversational applications such as video chat, video conferencing,
DVD and Blu-ray discs, video content acquisition and editing
systems, and camcorders of security applications.
[0004] Since the development of the block-based hybrid video coding
approach in the H.261 standard in 1990, new video coding techniques
and tools have been developed and have formed the basis for new
video coding standards. One of the goals of most of the video
coding standards was to achieve a bitrate reduction compared to its
predecessor without sacrificing picture quality. Further video
coding standards comprise MPEG-1 video, MPEG-2 video, ITU-T
H.262/MPEG-2, ITU-T H.263, ITU-T H.264/MPEG-4, Part 10, Advanced
Video Coding (AVC), ITU-T H.265, High Efficiency Video Coding
(HEVC), and extensions, e.g., scalability and/or three-dimensional
(3D) extensions, of these standards.
SUMMARY
[0005] According to a first aspect of the disclosure, an apparatus
for filtering a set of samples of an image using a filter with
adaptive multiplier coefficients represented by integer numbers is
provided. The apparatus comprises processing circuitry, which is
configured to group the multiplier coefficients of the filter into
at least two groups. The processing circuitry is further configured
to determine the value of each multiplier coefficient in a first
group so as to be allowed to assume any value in a first set of
allowed values of multiplier coefficients and to determine the
value of each multiplier coefficient in a second group so as to be
allowed to assume any value in a second set of allowed values of
multiplier coefficients, wherein at least one of the first and
second sets has at least one value that is not in the other set.
Still further, the processing circuitry is configured to filter the
set of samples of an image with the filter.
[0006] According to a second aspect of the disclosure, a method for
filtering a set of samples of an image using a filter with adaptive
multiplier coefficients represented by integer numbers is provided.
The method comprises the steps of grouping the multiplier
coefficients of the filter into at least two groups, determining
the value of each multiplier coefficient in a first group so as to
be allowed to assume any value in a first set of allowed values of
multiplier coefficients, determining the value of each multiplier
coefficient in a second group so as to be allowed to assume any
value in a second set of allowed values of multiplier coefficients
and of filtering the set of samples of an image with the filter. At
least one of the first and second sets has at least one value that
is not in the other set.
[0007] According to the present disclosure, a set of samples of an
image may, for instance, be a sample of a video signal or a still
image signal. The processing circuitry can be implemented by any
combination of software and/or hardware. The set of allowed values
may, in particular, be a predetermined set of allowed values.
Generally, aspects of the present disclosure are also applicable to
other sets of signal samples than images, for instance, to signals
including audio data.
[0008] It is a particular approach of the present disclosure to
restrict the values that can be assumed by the filter coefficients
of an adaptive multiplication filter in such a way that the
multiplication operation is simplified. Specifically, the filter
coefficients are grouped into at least two groups, and the
allowable values of one of the groups are restricted as compared to
a full range of integer values having absolute values up to a
predetermined maximum value (in particular, a full range of integer
values that can be represented in binary representation with a
predetermined number of bits) that is employed in another group.
This allows simplification of the multiplication operations for
filtering and thus renders the filtering operation more
efficient.
[0009] In accordance with embodiments, the allowed values of the
first set are all values within a range defined by a predetermined
maximum N.sub.max of the absolute value. Also, in accordance with
embodiments, the allowed values of the first set are all values
that can be represented by an L bit integer plus a sign bit,
wherein L is a positive integer. In the sense explained above, this
means that the group that is labeled "first group" can assume a
restricted "full range" of values in these embodiments. Further, in
accordance with embodiments, the allowed values of the second set
are all values that can be represented by an 1 bit integer plus a
sign bit, wherein l<ceil(log.sub.2(N.sub.max)) or l<L. In
this case, although both sets of allowed coefficients include a
"full range", the restriction resides in that the range of allowed
values in the second set is smaller than that in the first set.
[0010] In accordance with embodiments, the allowed values of the
second set are all values within a range defined by a predetermined
maximum P.sub.max (i.e. generally not the same as the above
identified N.sub.max) of the absolute value that are divisible by a
factor 2.sup.M, wherein M is a positive integer. For instance, in
case of M=1, this means that only even numbers are allowed within
the predetermined range, but odd numbers are not allowed.
[0011] In accordance with embodiments, the restriction in the
allowed values of the second set resides in the fact that the
binary representation of the absolute value with a predetermined
number of bits has at least one "zero". The restriction to a
predetermined number of bits (digits) in the binary representation
excludes leading (insignificant) zeros. More specifically, the
binary representation of the absolute value of each of the
multiplier coefficients in the second group includes at most two
"ones". Still more specifically, the binary representation of the
absolute value of the multiplier coefficients in the second group
includes at most one "one". As will be easily understood, the
simplification in performing the multiplication operation for
filtering and thus the gain and processing efficiency is the higher
the more zeroes (hence: the less "ones") are in the binary
representation of the allowed coefficient values. Thus the most
efficient case is when there's only one "one", whereas, for
instance, two allowed "ones" will still give a good result. Of
course, what is beneficial much depends on the details of the
situation, and, in particular, for large filters, also having three
or more "ones" may still be beneficial.
[0012] In accordance with embodiments, a set of samples of an image
means a set of samples of a video image. More specifically, the
apparatus may be configured individually to adapt the multiplier
coefficients for each picture and each pixel.
[0013] In accordance with a further particular aspect of the
present disclosure, an apparatus for encoding the current set of
samples of an image including a plurality of pixels is provided.
The apparatus comprises an encoder with a decoder for
reconstructing the current set and an apparatus according to the
first aspect of the present disclosure for filtering the
reconstructed set.
[0014] In accordance with embodiments, the encoding apparatus
further comprises processing circuitry, which is configured to map
the values of the multiplier coefficients to binary code words and
to include the code words into a bit stream for being transmitted
to a decoding apparatus.
[0015] More specifically, the length of the code words depends on
the number of distinct multiplier coefficient values. In other
words, there are as many codewords as possible filter coefficient
values. The codeword to value mapping (which is a one-to-one
mapping) can be a fixed mapping, or can change depending on
signaled side information.
[0016] In accordance with embodiments, the processing circuitry is
further configured to perform a prediction of the multiplier
coefficients of the filter and to determine residual multiplier
coefficients by comparing the actually determined values with the
predicted values resulting from the prediction. The mapping to
binary code words is then applied to the residual multiplier
coefficients. In this case, prediction control information might be
further included into the bit stream so that a decoding apparatus
receiving the bit stream is aware of the prediction method applied
and can reconstruct the multiplier coefficients of the filter from
the encoded residual multiplier coefficients. Alternatively, the
applied prediction method can be predefined, hence applied in the
same manner in the encoder and decoder without any transmitted side
information. Possible prediction methods may include but are not
limited to prediction using predefined filter predictors and
prediction from previously signaled filter coefficients. Because
the values of residual filter coefficients, expressing the
difference between an actual filter coefficient and the respective
predicted filter coefficient, are generally smaller in absolute
value than the actual coefficients, the amount and thus the size of
the codewords can be smaller, which additionally reduces
information to be signaled to the decoder.
[0017] Alternatively, the mapping of multiplier coefficients to
codewords for including in the bit stream can be performed on the
multiplier coefficients determined according to the first aspect of
the present disclosure, without performing prediction
processing.
[0018] In accordance with a still further aspect of the present
disclosure, an apparatus for decoding a coded current set of
samples of an image including a plurality of pixels is provided.
The apparatus comprises a decoder for reconstructing the current
set and an apparatus according to the first aspect of the present
disclosure for filtering the reconstructed set.
[0019] In accordance with embodiments, the processing circuitry of
the apparatus according to the first aspect of the present
disclosure is further configured to obtain multiplier coefficients
from binary codewords included in a received bit stream by applying
a mapping operation.
[0020] In particular, the obtained multiplier coefficients may be
the filter coefficients to be used for the filtering.
Alternatively, the obtained multiplier coefficients may be residual
multiplier coefficients representing the difference between the
actual coefficient values and multiplier coefficients predicted
according to a prediction scheme. The prediction scheme may be
indicated by prediction control information further included in the
received bit stream. In that case, the processing circuitry is
further configured to determine the values of the filter
coefficients by reconstructing them from the obtained residual
multiplier coefficients and the prediction control information.
Alternatively, the prediction scheme (prediction method) can be
predefined and hence applied in the same manner in the encoder and
decoder without any transmitted prediction control information. The
processing circuitry then determines the values of the filter
coefficients by reconstructing them from the obtained residual
multiplier coefficients.
[0021] In accordance with embodiments, the determination by the
processing circuitry further includes performing a determination as
to whether or not the determined values of the multiplier
coefficients, obtained directly from the received bit stream by the
mapping operation or by reconstruction from the obtained residual
multiplier coefficients are within the respective set of allowed
values, and, if not, converting the determined value to the nearest
value that is within the set of allowed values.
[0022] Thereby, it is guaranteed that the filter coefficients that
are applied on the reconstructed image samples obey the rules
according to the present disclosure.
[0023] Details of one or more embodiments are set forth in the
accompanying drawings and the description below. Other features,
objects, and advantages will be apparent from the description,
drawings, and claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0024] In the following, embodiments of the present disclosure are
described in more detail with reference to the attached figures and
drawings, in which:
[0025] FIG. 1 is a block diagram showing an example of a video
coding system configured to implement embodiments of the present
disclosure;
[0026] FIG. 2 is a block diagram showing an example of a video
encoder configured to implement embodiments of the present
disclosure;
[0027] FIG. 3 is a block diagram showing an example structure of a
video decoder configured to implement embodiments of the present
disclosure;
[0028] FIG. 4 shows an example of a filter kernel to which the
present disclosure can be applied;
[0029] FIG. 5 shows examples of typical filter shapes for adaptive
filters to which the present disclosure can be applied;
[0030] FIG. 6 illustrates an example of multiple fixed filters to
be applied in interpolation filtering, as a comparative
example;
[0031] FIG. 7 illustrates particular implementation examples of
embodiments of the present disclosure;
[0032] FIG. 8A illustrates an exemplary encoder side processing for
encoding and signaling of filter coefficients;
[0033] FIG. 8B illustrates an exemplary decoder side processing for
decoding and reconstructing filter coefficients;
[0034] FIG. 9 illustrates a particular implementation example of
another embodiment of the present disclosure;
[0035] FIG. 10 illustrates a particular implementation example of
yet another embodiment of the present disclosure;
[0036] FIG. 11 illustrates a particular implementation example of
yet another embodiment of the present disclosure and serves for an
illustration of the benefit achieved by means of the present
disclosure; and
[0037] FIG. 12 illustrates a further example of a filter kernel to
which the present disclosure can be applied.
[0038] In the drawings, identical reference signs refer to
identical or at least functionally equivalent features.
DETAILED DESCRIPTION
[0039] In the following description, reference is made to the
accompanying figures, which form part of the disclosure, and which
show, by way of illustration, specific aspects of embodiments of
the present disclosure or specific aspects in which embodiments of
the present disclosure may be used. It is understood that
embodiments of the present disclosure may be used in other aspects
and comprise structural or logical changes not depicted in the
figures. The following detailed description, therefore, is not to
be taken in a limiting sense, and the scope of the invention is
defined by the appended claims.
[0040] For instance, it is understood that a disclosure in
connection with a described method may also hold true for a
corresponding device or system configured to perform the method and
vice versa. For example, if one or a plurality of specific method
steps are described, a corresponding device may include one or a
plurality of units, e.g., functional units, to perform the
described one or plurality of method steps (e.g., one unit
performing the one or plurality of steps, or a plurality of units
each performing one or more of the plurality of steps), even if
such one or more units are not explicitly described or illustrated
in the figures. On the other hand, for example, if a specific
apparatus is described based on one or a plurality of units, e.g.,
functional units, a corresponding method may include one step to
perform the functionality of the one or plurality of units (e.g.,
one step performing the functionality of the one or plurality of
units, or a plurality of steps each performing the functionality of
one or more of the plurality of units), even if such one or
plurality of steps are not explicitly described or illustrated in
the figures. Further, it is understood that the features of the
various exemplary embodiments and/or aspects described herein may
be combined with each other, unless specifically noted
otherwise.
[0041] Video coding typically refers to the processing of a
sequence of pictures, which form the video or video sequence.
Instead of the term picture, the terms frame or image may be used
as synonyms in the field of video coding. Video coding comprises
two parts, video encoding and video decoding. Video encoding is
performed at the source side, typically comprising processing
(e.g., by compression) the original video pictures to reduce the
amount of data required for representing the video pictures (for
more efficient storage and/or transmission). Video decoding is
performed at the destination side and typically comprises the
inverse processing compared to the encoder to reconstruct the video
pictures. Embodiments referring to "coding" of video pictures (or
pictures in general, as will be explained later) shall be
understood to relate to both, "encoding" and "decoding" of video
pictures. The combination of the encoding part and the decoding
part is also referred to as CODEC (COding and DECoding).
[0042] In case of lossless video coding, the original video
pictures can be reconstructed, i.e. the reconstructed video
pictures have the same quality as the original video pictures
(assuming no transmission loss or other data loss during storage or
transmission). In case of lossy video coding, further compression,
e.g., by quantization, is performed, to reduce the amount of data
representing the video pictures, which cannot be completely
reconstructed at the decoder, i.e. the quality of the reconstructed
video pictures is lower or worse compared to the quality of the
original video pictures.
[0043] Several video coding standards since H.261 belong to the
group of "lossy hybrid video codecs" (i.e. combine spatial and
temporal prediction in the sample domain and 2D transform coding
for applying quantization in the transform domain). Each picture of
a video sequence is typically partitioned into a set of
non-overlapping blocks and the coding is typically performed on a
block level. In other words, at the encoder the video is typically
processed, i.e. encoded, on a block (video block) level, e.g., by
using spatial (intra picture) prediction and temporal (inter
picture) prediction to generate a prediction block, subtracting the
prediction block from the current block (block currently
processed/to be processed) to obtain a residual block, transforming
the residual block and quantizing the residual block in the
transform domain to reduce the amount of data to be transmitted
(compression), whereas at the decoder the inverse processing
compared to the encoder is applied to the encoded or compressed
block to reconstruct the current block for representation.
Furthermore, the encoder duplicates the decoder processing loop
such that both will generate identical predictions (e.g., intra-
and inter predictions) and/or re-constructions for processing, i.e.
coding, the subsequent blocks.
[0044] As video picture processing (also referred to as moving
picture processing) and still picture processing (the term
processing comprising coding), share many concepts and technologies
or tools, in the following the term "picture" or "image" and
equivalent the term "picture data" or "image data" is used to refer
to a video picture of a video sequence (as explained above) and/or
to a still picture to avoid unnecessary repetitions and
distinctions between video pictures and still pictures, where not
necessary. In case the description refers to still pictures (or
still images) only, the term "still picture" shall be used.
[0045] A schematic block diagram illustrating an embodiment of a
coding system 300 is given in FIG. 1, which will be described in
more detail below.
[0046] FIG. 2 is a block diagram showing an example structure of a
video encoder in which the embodiments of the present disclosure
can be implemented and which will be described in more detail below
as well.
[0047] In particular, the illustrated encoder 100 includes a "loop
filter" 120, wherein the filtering operation according to the
present disclosure can be applied. However, more generally, the
filtering operation is applicable at other locations of the codec,
for instance in an interpolation filter. Still more generally,
aspects of the present disclosure relate not only to video but also
to still picture coding.
[0048] FIG. 3 is a block diagram showing an example structure of a
video decoder in which the embodiments of the present disclosure
can be implemented and which will also be described in more detail
below. Specifically, aspects of the preset disclosure are
applicable, for instance, in the loop filter 220.
[0049] In the following, some information about adaptive filtering
will be summarized.
[0050] Adaptive filtering for video coding serves to minimize the
mean square error between originals and decoded samples by using a
Wiener-based adaptive filter. In particular, the proposed Adaptive
Loop Filter (ALF) is located at the last processing stage for each
picture and can be regarded as a tool to catch and fix artifacts
from previous stages. The suitable filter coefficients are
determined by the encoder and explicitly signaled to the
decoder.
[0051] General information about adaptive filtering can be found in
the article "Adaptive Loop Filtering for Video Coding", by
Chia-Yang Tsai, Ching-Yeh Chen, Tomoo Yamakage, In Suk Chong,
Yu-Wen Huang, Chih-Ming Fu, Takayuki Itoh, Takashi Watanabe,
Takeshi Chujoh, Marta Karczewicz, and Shaw-Min Lei, published in:
IEEE Journal of Selected Topics in Signal Processing (Volume: 7,
Issue: 6, December 2013).
[0052] The description given in the above document describes a
specific implementation of filtering operation with adaptive filter
coefficients. The general principles of the operation can be
described as follows.
[0053] Generally, the filtering equation reads:
R'(i,j)=.SIGMA..sub.k=-L/2.sup.L/2.SIGMA..sub.l=-L/2.sup.L/2f(k,l).times-
.R(i+k,j+l).
Herein, R(i,j) is a sample in a picture frame before filtering at
the coordinate (i,j). R'(i,j) is a sample in a picture frame after
filtering. f(k,l) are the filter coefficients.
[0054] An example filter kernel is depicted in FIG. 4. In this
example C20 is the center coordinate of the filter kernel (k=0,
l=0), and L is equal to 8.
[0055] In the example the filter kernel is symmetric around the
center. This may not be generally true.
[0056] In the case of using integer arithmetic, the filtering
equation may be written as:
R ' ( i , j ) = ( ( k = - L 2 L 2 l = - L 2 L 2 f ( k , l ) .times.
R ( i + k , j + l ) ) + offset ) >> N ##EQU00001##
Here, N is a number of a bit-shift of the output, i.e. the output
is divided by a normalization factor. In particular, N may be
predefined. The "offset" is a scalar to compensate for loss in the
integer arithmetic. In case of a bit shift by N, the offset may be
2.sup.(N-1). In the above equation, the filtering coefficients
f(k,l) can have values that are integers and not fractional
numbers. The implementation of the filtering equation according to
integer arithmetic is important in order to ensure precise
implementations in the hardware. The right shift operation
">>N" has the effect of division by 2.sup.N followed by a
rounding down operation.
[0057] Usually (but not necessarily), the following equation holds
true if no change in the average illumination level is desired.
2 N = k = - L 2 L 2 l = - L 2 L 2 f ( k , l ) ##EQU00002##
[0058] In the encoder, the filter coefficients are estimated by
minimizing the expected value of the error between the original and
the filter pixel.
E ( ( O ( i , j ) - k = - L 2 L 2 l = - L 2 L 2 f ( k , l ) .times.
R ( i + k , j + l ) ) 2 ) ##EQU00003##
In the above equation, O(i,j) denotes the sample of the original
picture.
[0059] FIG. 5 shows some typical exemplary filter shapes for
adaptive filters. The drawing on the left shows a 5.times.5 diamond
filter (13 tap filter with 7 unique coefficients), the middle
drawing--a 7.times.7 diamond filter (25 tap filter with 13 unique
coefficients), and the drawing on the right--a 9.times.9 diamond
filter (41 tap filter with 21 unique coefficients).
[0060] The term "adaptive" filtering refers to the fact that the
filtering process can be adjusted by the encoder. This concerns,
for instance, the filter shape, the filter size, the number of
filtering coefficients, and the values of filtering coefficients.
These data, also known as "filter hints", are signaled to the
decoder.
[0061] Adaptive filtering implies the following problem when
applied to filtering realizations that include multiplication,
i.e., wherein the filter coefficients are so-called multiplicative
or multiplier coefficients. In other words, the following problem,
which the present disclosure addresses, relates to filtering with
adaptive filter coefficients, wherein the filter coefficients that
are used in multiplication operation can be individually adapted
(modified). In this connection, individually means for each picture
(image, frame), and/or for each pixel, and/or each coefficient.
[0062] A problem is that the implementation of the multiplication
operation is costly, especially in dedicated hardware
implementations. The filter application requires a comparatively
large number of multiplication of filtering operations (for
instance, 41 multiplications per pixel in the case of a 9.times.9
diamond shaped filter, as shown in FIG. 4).
[0063] This is illustrated in more detail below.
[0064] Suppose we want to multiply two unsigned, eight-bit
integers. The filter coefficient is C and the sample pixel A.
[0065] The multiplication process can be decomposed into 8 one-bit
multiplications, each of which can be implemented as a bit shift
operation in binary arithmetic, and 7 addition operations as shown
below. Hence roughly 1 multiplication is equivalent to 7
additions.
[0066] The problem is that the multiplication process requires a
large amount of computation. Hence it is costly to implement in
dedicated hardware.
TABLE-US-00001 C[0]A[7] + C[1]A[7] C[1]A[6] + C[2]A[7] C[2]A[6]
C[2]A[5] + C[3]A[7] C[3]A[6] C[3]A[5] C[3]A[4] + C[7]A[7] C[7]A[6]
C[7]A[5] C[7]A[4] C[7]A[3] C[7]A[2] C[7]A[1] C[7]A[0] P[15] P[14]
P[13] P[12] P[11] P[10] P[9] P[8] P[7] C[0]A[6] C[0]A[5] C[0]A[4]
C[0]A[3] C[0]A[2] C[0]A[1] C[0]A[0] C[1]A[5] C[1]A[4] C[1]A[3]
C[1]A[2] C[1]A[1] C[1]A[0] 0 C[2]A[4] C[2]A[3] C[2]A[2] C[2]A[1]
C[2]A[0] 0 0 C[3]A[3] C[3]A[2] C[3]A[1] C[3]A[0] 0 0 0 . . . . . .
. . . 0 0 0 0 0 0 0 P[6] P[5] P[4] P[3] P[2] P[1] P[0]
[0067] Herein, the 8 bit unsigned filter coefficient C is shown in
binary representation, where C[0] is the least significant bit of
coefficient C and C[7] is the most significant bit. Similarly A[7],
A[6], . . . A[0] are the bits corresponding to the most significant
bit to the least significant bit in order. The operation P=C*A in
binary arithmetic is demonstrated and the result in shown in the
lowest line.
[0068] In the example of FIG. 4, the filter kernel includes 41
filter taps, meaning that in order to process a pixel sample, 41
multiplication operations are necessary.
[0069] It is pointed out that the present disclosure and the
above-described problem that it solves are related to adaptive
filtering with multiplier filter coefficients. The problem does not
apply to fixed filters, and, in particular, not to filtering
operations employing multiple fixed filters.
[0070] An example for employing multiple fixed filters is
interpolation filtering, for interpolating at fractional pixel
positions in the inter-prediction, which is illustrated in FIG.
6.
[0071] Many known codecs employ interpolation filtering using fixed
interpolation filters. Although the filter coefficients are fixed
for a filter, there are multiple filters for different fractional
positions (half pixel and quarter pixel positions in the drawing).
In the example, the whole filter set is adapted based on the motion
vector, but the filter coefficients are not adapted
individually.
[0072] In the figure, the large rounds correspond to actual sample
positions in an image, and the smaller rounds are the fractional
positions that are generated by application of the interpolation
filtering operation. In the specific example, there are 3
fractional positions (left quarter pel, half pel and right quarter
pel) positions in between two actual image sample positions. On the
left-hand side of the drawing, an interpolation filter applied for
interpolating half pixel (half-pel) positions is shown. The
right-hand side of the drawing illustrates an interpolation filter
to be used for quarter pixel (quarter-pel) positions. Although
these filters are different from each other, each interpolation
filter is a fixed filter. As indicated, the example of FIG. 6 has
been provided for illustrative purposes only.
[0073] The present disclosure provides an improved concept of
multiplicative adaptive filtering, which can simplify the
multiplication operation and reduce the multiplication operation
effort.
[0074] In the following embodiments of an encoder 100, a decoder
200 and a coding system 300 are described based on FIGS. 1 to 3
(before describing embodiments of the present disclosure in more
detail based on FIGS. 7 to 9).
[0075] FIG. 1 is a conceptional or schematic block diagram
illustrating an embodiment of a coding system 300, e.g., a picture
coding system 300, wherein the coding system 300 comprises a source
device 310 configured to provide encoded data 330, e.g., an encoded
picture 330, e.g., to a destination device 320 for decoding the
encoded data 330.
[0076] The source device 310 comprises an encoder 100 or encoding
unit 100, and may additionally, i.e. optionally, comprise a picture
source 312, a pre-processing unit 314, e.g., a picture
pre-processing unit 314, and a communication interface or
communication unit 318.
[0077] The picture source 312 may comprise or be any kind of
picture capturing device, for example for capturing a real-world
picture, and/or any kind of a picture generating device, for
example a computer-graphics processor for generating a computer
animated picture, or any kind of device for obtaining and/or
providing a real-world picture, a computer animated picture (e.g.,
a screen content, a virtual reality (VR) picture) and/or any
combination thereof (e.g., an augmented reality (AR) picture). In
the following, all these kinds of pictures or images and any other
kind of picture or image will be referred to as "picture", "image",
or "picture data", or "image data", unless specifically described
otherwise, while the previous explanations with regard to the terms
"picture" or "image" covering "video pictures" and "still pictures"
still hold true, unless explicitly specified differently.
[0078] A (digital) picture is or can be regarded as a
two-dimensional array or matrix of samples with intensity values. A
sample in the array may also be referred to as pixel (short form of
picture element) or a pel. The number of samples in horizontal and
vertical direction (or axis) of the array or picture define the
size and/or resolution of the picture. For representation of color,
typically three color components are employed, i.e. the picture may
be represented or include three sample arrays. In RGB format or
color space a picture comprises a corresponding red, green and blue
sample array. However, in video coding each pixel is typically
represented in a luminance/chrominance format or color space, e.g.,
YCbCr, which comprises a luminance component indicated by Y
(sometimes also L is used instead) and two chrominance components
indicated by Cb and Cr. The luminance (or short luma) component Y
represents the brightness or grey level intensity (e.g., like in a
grey-scale picture), while the two chrominance (or short chroma)
components Cb and Cr represent the chromaticity or color
information components. Accordingly, a picture in YCbCr format
comprises a luminance sample array of luminance sample values (Y),
and two chrominance sample arrays of chrominance values (Cb and
Cr). Pictures in RGB format may be converted or transformed into
YCbCr format and vice versa, the process is also known as color
transformation or conversion. If a picture is monochrome, the
picture may comprise only a luminance sample array.
[0079] The picture source 312 may be, for example a camera for
capturing a picture, a memory, e.g., a picture memory, comprising
or storing a previously captured or generated picture, and/or any
kind of interface (internal or external) to obtain or receive a
picture. The camera may be, for example, a local or integrated
camera integrated in the source device, the memory may be a local
or integrated memory, e.g., integrated in the source device. The
interface may be, for example, an external interface to receive a
picture from an external video source, for example an external
picture capturing device like a camera, an external memory, or an
external picture generating device, for example an external
computer-graphics processor, computer or server. The interface can
be any kind of interface, e.g., a wired or wireless interface, an
optical interface, according to any proprietary or standardized
interface protocol. The interface for obtaining the picture data
313 may be the same interface as or a part of the communication
interface 318.
[0080] Interfaces between units within each device include cable
connections, USB interfaces, Communication interfaces 318 and 322
between the source device 310 and the destination device 320
include cable connections, USB interfaces, radio interfaces.
[0081] In distinction to the pre-processing unit 314 and the
processing performed by the pre-processing unit 314, the picture or
picture data 313 may also be referred to as raw picture or raw
picture data 313.
[0082] Pre-processing unit 314 is configured to receive the (raw)
picture data 313 and to perform pre-processing on the picture data
313 to obtain a pre-processed picture 315 or pre-processed picture
data 315. Pre-processing performed by the pre-processing unit 314
may, e.g., comprise trimming, color format conversion (e.g., from
RGB to YCbCr), color correction, or de-noising.
[0083] The encoder 100 is configured to receive the pre-processed
picture data 315 and provide encoded picture data 171 (further
details will be described, e.g., based on FIG. 2).
[0084] Communication interface 318 of the source device 310 may be
configured to receive the encoded picture data 171 and to directly
transmit it to another device, e.g., the destination device 320 or
any other device, for storage or direct reconstruction, or to
process the encoded picture data 171 for respectively before
storing the encoded data 330 and/or transmitting the encoded data
330 to another device, e.g., the destination device 320 or any
other device for decoding or storing.
[0085] The destination device 320 comprises a decoder 200 or
decoding unit 200, and may additionally, i.e. optionally, comprise
a communication interface or communication unit 322, a
post-processing unit 326 and a display device 328.
[0086] The communication interface 322 of the destination device
320 is configured to receive the encoded picture data 171 or the
encoded data 330, e.g., directly from the source device 310 or from
any other source, e.g., a memory, e.g., an encoded picture data
memory.
[0087] The communication interface 318 and the communication
interface 322 may be configured to transmit respectively receive
the encoded picture data 171 or encoded data 330 via a direct
communication link between the source device 310 and the
destination device 320, e.g., a direct wired or wireless
connection, including optical connection or via any kind of
network, e.g., a wired or wireless network or any combination
thereof, or any kind of private and public network, or any kind of
combination thereof.
[0088] The communication interface 318 may be, e.g., configured to
package the encoded picture data 171 into an appropriate format,
e.g., packets, for transmission over a communication link or
communication network, and may further comprise data loss
protection.
[0089] The communication interface 322, forming the counterpart of
the communication interface 318, may be, e.g., configured to
de-package the encoded data 330 to obtain the encoded picture data
171 and may further be configured to perform data loss protection
and data loss recovery, e.g., comprising error concealment.
[0090] Both, communication interface 318 and communication
interface 322 may be configured as unidirectional communication
interfaces as indicated by the arrow for the encoded picture data
330 in FIG. 1 pointing from the source device 310 to the
destination device 320, or bi-directional communication interfaces,
and may be configured, e.g., to send and receive messages, e.g., to
set up a connection, to acknowledge and/or re-send lost or delayed
data including picture data, and exchange any other information
related to the communication link and/or data transmission, e.g.,
encoded picture data transmission.
[0091] The decoder 200 is configured to receive the encoded picture
data 171 and provide decoded picture data 231 or a decoded picture
231 (further details will be described, e.g., based on FIG. 9).
[0092] The post-processor 326 of destination device 320 is
configured to post-process the decoded picture data 231, e.g., the
decoded picture 231, to obtain post-processed picture data 327,
e.g., a post-processed picture 327. The post-processing performed
by the post-processing unit 326 may comprise, e.g., color format
conversion (e.g., from YCbCr to RGB), color correction, trimming,
or re-sampling, or any other processing, e.g., for preparing the
decoded picture data 231 for display, e.g., by display device
328.
[0093] The display device 328 of the destination device 320 is
configured to receive the post-processed picture data 327 for
displaying the picture, e.g., to a user or viewer. The display
device 328 may be or comprise any kind of display for representing
the reconstructed picture, e.g., an integrated or external display
or monitor. The displays may, e.g., comprise cathode ray tubes
(CRT), liquid crystal displays (LCD), plasma displays, organic
light emitting diodes (OLED) displays or any kind of other display,
such as projectors, holographic displays, apparatuses to generate
holograms . . .
[0094] Although FIG. 1 depicts the source device 310 and the
destination device 320 as separate devices, embodiments of devices
may also comprise both or both functionalities, the source device
310 or corresponding functionality and the destination device 320
or corresponding functionality. In such embodiments, the source
device 310 or corresponding functionality and the destination
device 320 or corresponding functionality may be implemented using
the same hardware and/or software, or by separate hardware and/or
software, or any combination thereof.
[0095] As will be apparent for the skilled person based on the
description, the existence and (exact) split of functionalities of
the different units or functionalities within the source device 310
and/or destination device 320 as shown in FIG. 1 may vary depending
on the actual device and application.
[0096] In the following, a few non-limiting examples for the coding
system 300, the source device 310 and/or destination device 320
will be provided.
[0097] Various electronic products, such as a smartphone, a tablet,
or a handheld camera with integrated display, may be seen as
examples for a coding system 300. They contain a display device 328
and most of them contain an integrated camera, i.e. a picture
source 312, as well. Picture data taken by the integrated camera is
processed and displayed. The processing may include encoding and
decoding of the picture data internally. In addition, the encoded
picture data may be stored in an integrated memory.
[0098] Alternatively, these electronic products may have wired or
wireless interfaces to receive picture data from external sources,
such as the internet or external cameras, or to transmit the
encoded picture data to external displays or storage units.
[0099] On the other hand, set-top boxes do not contain an
integrated camera or a display but perform picture processing of
received picture data for display on an external display device.
Such a set-top box may be embodied by a chipset, for example.
[0100] Alternatively, a device similar to a set-top box may be
included in a display device, such as a TV set with integrated
display.
[0101] Surveillance cameras without an integrated display
constitute a further example. They represent a source device with
an interface for the transmission of the captured and encoded
picture data to an external display device or an external storage
device.
[0102] Devices such as smart glasses or 3D glasses, for instance
used for AR or VR, represent a destination device 320. They receive
the encoded picture data and display them.
[0103] Therefore, the source device 310 and the destination device
320 as shown in FIG. 1 are just example embodiments of the present
disclosure and embodiments of the present disclosure are not
limited to those shown in FIG. 1.
[0104] Source device 310 and destination device 320 may comprise
any of a wide range of devices, including any kind of handheld or
stationary devices, e.g., notebook or laptop computers, mobile
phones, smart phones, tablets or tablet computers, cameras, desktop
computers, set-top boxes, televisions, display devices, digital
media players, video gaming consoles, video streaming devices,
broadcast receiver device, or the like. For large-scale
professional encoding and decoding, the source device 310 and/or
the destination device 320 may additionally comprise servers and
work stations, which may be included in large networks. These
devices may use no or any kind of operating system.
Encoder & Encoding Method
[0105] FIG. 2 shows a schematic/conceptual block diagram of an
embodiment of an encoder 100, e.g., a picture encoder 100, which
comprises an input 102, a residual calculation unit 104, a
transformation unit 106, a quantization unit 108, an inverse
quantization unit 110, and inverse transformation unit 112, a
reconstruction unit 114, a buffer 116, a loop filter 120, a decoded
picture buffer (DPB) 130, a prediction unit 160, which includes an
inter estimation unit 142, an inter prediction unit 144, an
intra-estimation unit 152, an intra-prediction unit 154 and a mode
selection unit 162, an entropy encoding unit 170, and an output
172. A video encoder 100 as shown in FIG. 2 may also be referred to
as hybrid video encoder or a video encoder according to a hybrid
video codec. Each unit may consist of a processor and a
non-transitory memory to perform its processing steps by executing
a code stored in the non-transitory memory by the processor.
[0106] For example, the residual calculation unit 104, the
transformation unit 106, the quantization unit 108, and the entropy
encoding unit 170 form a forward signal path of the encoder 100,
whereas, for example, the inverse quantization unit 110, the
inverse transformation unit 112, the reconstruction unit 114, the
buffer 116, the loop filter 120, the decoded picture buffer (DPB)
130, the inter prediction unit 144, and the intra-prediction unit
154 form a backward signal path of the encoder, wherein the
backward signal path of the encoder corresponds to the signal path
of the decoder to provide inverse processing for identical
reconstruction and prediction (see decoder 200 in FIG. 3).
[0107] The encoder is configured to receive, e.g., by input 102, a
picture 101 or a picture block 103 of the picture 101, e.g.,
picture of a sequence of pictures forming a video or video
sequence. The picture block 103 may also be referred to as current
picture block or picture block to be coded, and the picture 101 as
current picture or picture to be coded (in particular in video
coding to distinguish the current picture from other pictures,
e.g., previously encoded and/or decoded pictures of the same video
sequence, i.e. the video sequence which also comprises the current
picture).
Partitioning
[0108] Embodiments of the encoder 100 may comprise a partitioning
unit, e.g., which may also be referred to as picture partitioning
unit, configured to partition the picture 103 into a plurality of
blocks, e.g., blocks like block 103, typically into a plurality of
non-overlapping blocks. The partitioning unit may be configured to
use the same block size for all pictures of a video sequence and
the corresponding grid defining the block size, or to change the
block size between pictures or subsets or groups of pictures, and
partition each picture into the corresponding blocks.
[0109] Each block of the plurality of blocks may have square
dimensions or more general rectangular dimensions. Blocks being
picture areas with non-rectangular shapes may not appear.
[0110] Like the picture 101, the block 103 again is or can be
regarded as a two-dimensional array or matrix of samples with
intensity values (sample values), although of smaller dimension
than the picture 101. In other words, the block 103 may comprise,
e.g., one sample array (e.g., a luma array in case of a monochrome
picture 101) or three sample arrays (e.g., a luma and two chroma
arrays in case of a color picture 101) or any other number and/or
kind of arrays depending on the color format applied. The number of
samples in horizontal and vertical direction (or axis) of the block
103 define the size of block 103.
[0111] Encoder 100 as shown in FIG. 2 is configured to encode the
picture 101 block by block, e.g., the encoding and prediction is
performed per block 103.
Residual Calculation
[0112] The residual calculation unit 104 is configured to calculate
a residual block 105 based on the picture block 103 and a
prediction block 165 (further details about the prediction block
165 are provided later), e.g., by subtracting sample values of the
prediction block 165 from sample values of the picture block 103,
sample by sample (pixel by pixel) to obtain the residual block 105
in the sample domain.
Transformation
[0113] The transformation unit 106 is configured to apply a
transformation, e.g., a spatial frequency transform or a linear
spatial transform, e.g., a discrete cosine transform (DCT) or
discrete sine transform (DST), on the sample values of the residual
block 105 to obtain transformed coefficients 107 in a transform
domain. The transformed coefficients 107 may also be referred to as
transformed residual coefficients and represent the residual block
105 in the transform domain.
[0114] The transformation unit 106 may be configured to apply
integer approximations of DCT/DST, such as the core transforms
specified for HEVC/H.265. Compared to an orthonormal DCT transform,
such integer approximations are typically scaled by a certain
factor. In order to preserve the norm of the residual block which
is processed by forward and inverse transforms, additional scaling
factors are applied as part of the transform process. The scaling
factors are typically chosen based on certain constraints like
scaling factors being a power of two for shift operation, bit depth
of the transformed coefficients, tradeoff between accuracy and
implementation costs, etc. Specific scaling factors are, for
example, specified for the inverse transform, e.g., by inverse
transformation unit 212, at a decoder 200 (and the corresponding
inverse transform, e.g., by inverse transformation unit 112 at an
encoder 100) and corresponding scaling factors for the forward
transform, e.g., by transformation unit 106, at an encoder 100 may
be specified accordingly.
Quantization
[0115] The quantization unit 108 is configured to quantize the
transformed coefficients 107 to obtain quantized coefficients 109,
e.g., by applying scalar quantization or vector quantization. The
quantized coefficients 109 may also be referred to as quantized
residual coefficients 109. For example for scalar quantization,
different scaling may be applied to achieve finer or coarser
quantization. Smaller quantization step sizes correspond to finer
quantization, whereas larger quantization step sizes correspond to
coarser quantization. The applicable quantization step size may be
indicated by a quantization parameter (QP). The quantization
parameter may for example be an index to a predefined set of
applicable quantization step sizes. For example, small quantization
parameters may correspond to fine quantization (small quantization
step sizes) and large quantization parameters may correspond to
coarse quantization (large quantization step sizes) or vice versa.
The quantization may include division by a quantization step size
and corresponding or inverse dequantization, e.g., by inverse
quantization 110, may include multiplication by the quantization
step size. Embodiments according to HEVC (High-Efficiency Video
Coding), may be configured to use a quantization parameter to
determine the quantization step size. Generally, the quantization
step size may be calculated based on a quantization parameter using
a fixed point approximation of an equation including division.
Additional scaling factors may be introduced for quantization and
dequantization to restore the norm of the residual block, which
might get modified because of the scaling used in the fixed point
approximation of the equation for quantization step size and
quantization parameter. In one example implementation, the scaling
of the inverse transform and dequantization might be combined.
Alternatively, customized quantization tables may be used and
signaled from an encoder to a decoder, e.g., in a bit stream. The
quantization is a lossy operation, wherein the loss increases with
increasing quantization step sizes.
[0116] Embodiments of the encoder 100 (or respectively of the
quantization unit 108) may be configured to output the quantization
settings including quantization scheme and quantization step size,
e.g., by means of the corresponding quantization parameter, so that
a decoder 200 may receive and apply the corresponding inverse
quantization. Embodiments of the encoder 100 (or quantization unit
108) may be configured to output the quantization scheme and
quantization step size, e.g., directly or entropy encoded via the
entropy encoding unit 170 or any other entropy coding unit.
[0117] The inverse quantization unit 110 is configured to apply the
inverse quantization of the quantization unit 108 on the quantized
coefficients to obtain dequantized coefficients 111, e.g., by
applying the inverse of the quantization scheme applied by the
quantization unit 108 based on or using the same quantization step
size as the quantization unit 108. The dequantized coefficients 111
may also be referred to as dequantized residual coefficients 111
and correspond--although typically not identical to the transformed
coefficients due to the loss by quantization--to the transformed
coefficients 108.
[0118] The inverse transformation unit 112 is configured to apply
the inverse transformation of the transformation applied by the
transformation unit 106, e.g., an inverse discrete cosine transform
(DCT) or inverse discrete sine transform (DST), to obtain an
inverse transformed block 113 in the sample domain. The inverse
transformed block 113 may also be referred to as inverse
transformed dequantized block 113 or inverse transformed residual
block 113.
[0119] The reconstruction unit 114 is configured to combine the
inverse transformed block 113 and the prediction block 165 to
obtain a reconstructed block 115 in the sample domain, e.g., by
sample wise adding the sample values of the decoded residual block
113 and the sample values of the prediction block 165.
[0120] The buffer unit 116 (or short "buffer" 116), e.g., a line
buffer 116, is configured to buffer or store the reconstructed
block and the respective sample values, for example for intra
estimation and/or intra prediction. In further embodiments, the
encoder may be configured to use unfiltered reconstructed blocks
and/or the respective sample values stored in buffer unit 116 for
any kind of estimation and/or prediction.
[0121] Embodiments of the encoder 100 may be configured such that,
e.g., the buffer unit 116 is not only used for storing the
reconstructed blocks 115 for intra estimation 152 and/or intra
prediction 154 but also for the loop filter unit 120, and/or such
that, e.g., the buffer unit 116 and the decoded picture buffer unit
130 form one buffer. Further embodiments may be configured to use
filtered blocks 121 and/or blocks or samples from the decoded
picture buffer 130 (as input or basis for intra estimation 152
and/or intra prediction 154.
[0122] The loop filter unit 120 (or short "loop filter" 120), is
configured to filter the reconstructed block 115 to obtain a
filtered block 121, e.g., by applying a de-blocking sample-adaptive
offset (SAO) filter or other filters, e.g., sharpening or smoothing
filters or collaborative filters. The filtered block 121 may also
be referred to as filtered reconstructed block 121.
[0123] Embodiments of the loop filter unit 120 may comprise a
filter analysis unit and the actual filter unit, wherein the filter
analysis unit is configured to determine loop filter parameters for
the actual filter. The filter analysis unit may be configured to
apply fixed pre-determined filter parameters to the actual loop
filter, adaptively select filter parameters from a set of
predetermined filter parameters or adaptively calculate filter
parameters for the actual loop filter.
[0124] Embodiments of the loop filter unit 120 may comprise (one or
a plurality of filters (such as loop filter components and/or
subfilters), e.g., one or more of different kinds or types of
filters, e.g., connected in series or in parallel or in any
combination thereof, wherein each of the filters may comprise
individually or jointly with other filters of the plurality of
filters a filter analysis unit to determine the respective loop
filter parameters, e.g., as described in the previous
paragraph.
[0125] Embodiments of the encoder 100 (respectively loop filter
unit 120) may be configured to output the loop filter parameters,
e.g., directly or entropy encoded via the entropy encoding unit 170
or any other entropy coding unit, so that, e.g., a decoder 200 may
receive and apply the same loop filter parameters for decoding.
[0126] The decoded picture buffer (DPB) 130 is configured to
receive and store the filtered block 121. The decoded picture
buffer 130 may be further configured to store other previously
filtered blocks, e.g., previously reconstructed and filtered blocks
121, of the same current picture or of different pictures, e.g.,
previously reconstructed pictures, and may provide complete
previously reconstructed, i.e. decoded, pictures (and corresponding
reference blocks and samples) and/or a partially reconstructed
current picture (and corresponding reference blocks and samples),
for example for inter estimation and/or inter prediction.
[0127] Further embodiments of the present disclosure may also be
configured to use the previously filtered blocks and corresponding
filtered sample values of the decoded picture buffer 130 for any
kind of estimation or prediction, e.g., intra estimation and
prediction as well as inter estimation and prediction.
[0128] The prediction unit 160, also referred to as block
prediction unit 160, is configured to receive or obtain the picture
block 103 (current picture block 103 of the current picture 101)
and decoded or at least reconstructed picture data, e.g., reference
samples of the same (current) picture from buffer 116 and/or
decoded picture data 231 from one or a plurality of previously
decoded pictures from decoded picture buffer 130, and to process
such data for prediction, i.e. to provide a prediction block 165,
which may be an inter-predicted block 145 or an intra-predicted
block 155.
[0129] Mode selection unit 162 may be configured to select a
prediction mode (e.g., an intra or inter prediction mode) and/or a
corresponding prediction block 145 or 155 to be used as prediction
block 165 for the calculation of the residual block 105 and for the
reconstruction of the reconstructed block 115.
[0130] Embodiments of the mode selection unit 162 may be configured
to select the prediction mode (e.g., from those supported by
prediction unit 160), which provides the best match or in other
words the minimum residual (minimum residual means better
compression for transmission or storage), or a minimum signaling
overhead (minimum signaling overhead means better compression for
transmission or storage), or which considers or balances both. The
mode selection unit 162 may be configured to determine the
prediction mode based on rate distortion optimization (RDO), i.e.
select the prediction mode which provides a minimum rate distortion
optimization or which associated rate distortion at least fulfills
a prediction mode selection criterion.
[0131] In the following the prediction processing (e.g., prediction
unit 160) and mode selection (e.g., by mode selection unit 162)
performed by an example encoder 100 will be explained in more
detail.
[0132] As described above, encoder 100 is configured to determine
or select the best or an optimum prediction mode from a set of
(pre-determined) prediction modes. The set of prediction modes may
comprise, e.g., intra-prediction modes and/or inter-prediction
modes.
[0133] The set of intra-prediction modes may comprise 32 different
intra-prediction modes, e.g., non-directional modes like DC (or
mean) mode and planar mode, or directional modes, e.g., as defined
in H.264, or may comprise 65 different intra-prediction modes,
e.g., non-directional modes like DC (or mean) mode and planar mode,
or directional modes, e.g., as defined in H.265.
[0134] The set of (or possible) inter-prediction modes depend on
the available reference pictures (i.e. previous at least partially
decoded pictures, e.g., stored in DPB 230) and other
inter-prediction parameters, e.g., whether the whole reference
picture or only a part, e.g., a search window area around the area
of the current block, of the reference picture is used for
searching for a best matching reference block, and/or e.g., whether
pixel interpolation is applied, e.g., half/semi-pel and/or
quarter-pel interpolation, or not.
[0135] Additional to the above prediction modes, skip mode and/or
direct mode may be applied.
[0136] The prediction unit 160 may be further configured to
partition the block 103 into smaller block partitions or
sub-blocks, e.g., iteratively using quad-tree-partitioning (QT),
binary partitioning (BT) or triple-tree-partitioning (TT) or any
combination thereof, and to perform, e.g., the prediction for each
of the block partitions or sub-blocks, wherein the mode selection
comprises the selection of the tree-structure of the partitioned
block 103 and the prediction modes applied to each of the block
partitions or sub-blocks.
[0137] The inter estimation unit 142, also referred to as inter
picture estimation unit 142, is configured to receive or obtain the
picture block 103 (current picture block 103 of the current picture
101) and a decoded picture 231, or at least one or a plurality of
previously reconstructed blocks, e.g., reconstructed blocks of one
or a plurality of other/different previously decoded pictures 231,
for inter estimation (or "inter picture estimation"). e.g., a video
sequence may comprise the current picture and the previously
decoded pictures 231, or in other words, the current picture and
the previously decoded pictures 231 may be part of or form a
sequence of pictures forming a video sequence.
[0138] The encoder 100 may, e.g., be configured to select
(obtain/determine) a reference block from a plurality of reference
blocks of the same or different pictures of the plurality of other
pictures and provide a reference picture (or reference picture
index, . . . ) and/or an offset (spatial offset) between the
position (x, y coordinates) of the reference block and the position
of the current block as inter estimation parameters 143 to the
inter prediction unit 144. This offset is also called motion vector
(MV). The inter estimation is also referred to as motion estimation
(ME) and the inter prediction also motion prediction (MP).
[0139] The inter prediction unit 144 is configured to obtain, e.g.,
receive, an inter prediction parameter 143 and to perform inter
prediction based on or using the inter prediction parameter 143 to
obtain an inter prediction block 145.
[0140] Although FIG. 2 shows two distinct units (or steps) for the
inter-coding, namely inter estimation 142 and inter prediction 152,
both functionalities may be performed as one (inter estimation
typically requires/comprises calculating an/the inter prediction
block, i.e. the or a "kind of" inter prediction 154), e.g., by
testing all possible or a predetermined subset of possible inter
prediction modes iteratively while storing the currently best inter
prediction mode and respective inter prediction block, and using
the currently best inter prediction mode and respective inter
prediction block as the (final) inter prediction parameter 143 and
inter prediction block 145 without performing another time the
inter prediction 144.
[0141] The intra estimation unit 152 is configured to obtain, e.g.,
receive, the picture block 103 (current picture block) and one or a
plurality of previously reconstructed blocks, e.g., reconstructed
neighbor blocks, of the same picture for intra estimation. The
encoder 100 may, e.g., be configured to select (obtain/determine)
an intra prediction mode from a plurality of intra prediction modes
and provide it as intra estimation parameter 153 to the intra
prediction unit 154.
[0142] Embodiments of the encoder 100 may be configured to select
the intra-prediction mode based on an optimization criterion, e.g.,
minimum residual (e.g., the intra-prediction mode providing the
prediction block 155 most similar to the current picture block 103)
or minimum rate distortion.
[0143] The intra prediction unit 154 is configured to determine
based on the intra prediction parameter 153, e.g., the selected
intra prediction mode 153, the intra prediction block 155.
[0144] Although FIG. 2 shows two distinct units (or steps) for the
intra-coding, namely intra estimation 152 and intra prediction 154,
both functionalities may be performed as one (intra estimation
typically requires/comprises calculating the intra prediction
block, i.e. the or a "kind of" intra prediction 154), e.g., by
testing all possible or a predetermined subset of possible
intra-prediction modes iteratively while storing the currently best
intra prediction mode and respective intra prediction block, and
using the currently best intra prediction mode and respective intra
prediction block as the (final) intra prediction parameter 153 and
intra prediction block 155 without performing another time the
intra prediction 154.
[0145] The entropy encoding unit 170 is configured to apply an
entropy encoding algorithm or scheme (e.g., a variable length
coding (VLC) scheme, an context adaptive VLC scheme (CALVC), an
arithmetic coding scheme, a context adaptive binary arithmetic
coding (CABAC)) on the quantized residual coefficients 109, inter
prediction parameters 143, intra prediction parameter 153, and/or
loop filter parameters, individually or jointly (or not at all) to
obtain encoded picture data 171 which can be output by the output
172, e.g., in the form of an encoded bit stream 171.
Decoder
[0146] FIG. 3 shows an exemplary video decoder 200 configured to
receive encoded picture data (e.g., encoded bit stream) 171, e.g.,
encoded by encoder 100, to obtain a decoded picture 231.
[0147] The decoder 200 comprises an input 202, an entropy decoding
unit 204, an inverse quantization unit 210, an inverse
transformation unit 212, a reconstruction unit 214, a buffer 216, a
loop filter 220, a decoded picture buffer 230, a prediction unit
260, which includes an inter prediction unit 244, an intra
prediction unit 254, and a mode selection unit 260, and an output
232.
[0148] The entropy decoding unit 204 is configured to perform
entropy decoding to the encoded picture data 171 to obtain, e.g.,
quantized coefficients 209 and/or decoded coding parameters, e.g.,
(decoded) any or all of inter prediction parameters 143, intra
prediction parameter 153, and/or loop filter parameters.
[0149] In embodiments of the decoder 200, the inverse quantization
unit 210, the inverse transformation unit 212, the reconstruction
unit 214, the buffer 216, the loop filter 220, the decoded picture
buffer 230, the prediction unit 260 and the mode selection unit 260
are configured to perform the inverse processing of the encoder 100
(and the respective functional units) to decode the encoded picture
data 171.
[0150] In particular, the inverse quantization unit 210 may be
identical in function to the inverse quantization unit 110, the
inverse transformation unit 212 may be identical in function to the
inverse transformation unit 112, the reconstruction unit 214 may be
identical in function reconstruction unit 114, the buffer 216 may
be identical in function to the buffer 116, the loop filter 220 may
be identical in function to the loop filter 220 (with regard to the
actual loop filter as the loop filter 220 typically does not
comprise a filter analysis unit to determine the filter parameters
based on the original image 101 or block 103 but receives
(explicitly or implicitly) or obtains the filter parameters used
for encoding, e.g., from entropy decoding unit 204), and the
decoded picture buffer 230 may be identical in function to the
decoded picture buffer 130.
[0151] The prediction unit 260 may comprise an inter prediction
unit 244 and an intra prediction unit 254, wherein the inter
prediction unit 244 may be identical in function to the inter
prediction unit 144, and the intra prediction unit 254 may be
identical in function to the intra prediction unit 154. The
prediction unit 260 and the mode selection unit 262 are typically
configured to perform the block prediction and/or obtain the
predicted block 265 from the encoded data 171 only (without any
further information about the original image 101) and to receive or
obtain (explicitly or implicitly) the prediction parameters 143 or
153 and/or the information about the selected prediction mode,
e.g., from the entropy decoding unit 204.
[0152] The decoder 200 is configured to output the decoded picture
231, e.g., via output 232, for presentation or viewing to a
user.
[0153] Referring back to FIG. 1, the decoded picture 231 output
from the decoder 200 may be post-processed in the post-processor
326. The resulting post-processed picture 327 may be transferred to
an internal or external display device 328 and displayed.
Further Details of Embodiments
[0154] Embodiments of the present disclosure restrict the values
that can be assumed by the filter coefficients of an adaptive
multiplicative filter in such a way that the multiplication
operation is simplified. The filtering of a set of signal samples
of an image uses a filter with adaptive multiplier coefficients,
where the multiplier coefficients are represented by integer
numbers. Given that the highest value of the absolute value of a
coefficient C is N, the binary representation of N requires
L=ceil(log.sub.2(N)) binary digits. In other words, with L binary
digits, absolute coefficient values from zero (L "zeroes") to
2.sup.L-1 (L "ones") can be expressed (the sign of the coefficient
is represented by a separate sign bit). According to the particular
approach of the present disclosure, the overall amount of
coefficients of the filter is grouped into at least two groups and
the set of allowed values is restricted for one group as compared
to the other group. In other words, not all of the filter
coefficients are allowed to assume all values that are generally
possible for a particular filter.
[0155] In the following, particular embodiments of implementation
of the present disclosure will be described in detail.
[0156] It is noted that the exemplary values of parameters given
below are for illustrative purposes only, and the skilled person is
aware that they may be replaced within any other possible values
that are within the scope of the appended claims.
[0157] Generally, the filter coefficients are implemented using
finite precision. A filter coefficient is represented using L bits,
together with an optional sign bit. The amount of bits L depends on
the maximum absolute value of the coefficient. Specifically, given
that the highest value of the absolute value of a coefficient C is
N, the binary representation of N requires L=ceil(log.sub.2(N))
binary digits.
[0158] The ceil(x) function, also denoted as [x] or ceiling(x),
maps x to the least integer greater than or equal to x.
[0159] In the following, exemplary embodiments will be described
with reference to FIG. 7.
[0160] In a first example, in a first step, the coefficients are
grouped into two groups. In the drawing, the first group
corresponds to the coefficient positions indicated by open circles
in the central portion of the filter and the second group
corresponds to the coefficient positions indicated by filled black
circles in the drawing, in the peripheral portion of the
filter.
[0161] The filter coefficients in the first group can assume any
value in a predetermined range. In the illustrated example, it is
assumed that the range corresponds to a set "S1", wherein S1=[-511,
. . . , 511]. This corresponds to an overall number of bits
(excluding the sign bit) of L=9.
[0162] The filter coefficients in the second group can assume any
value in a set "S2", wherein S2 is a subset of S1. More
specifically, in an example, the set S2 is defined as S2=[-63, . .
. , 63], i.e. also a "full range" of values, but only those that
can be represented with a restricted number of bits L=6 (again
excluding the sign bit) only.
[0163] The benefit of the example is that for the set S2, i.e. for
the coefficients in the second group, 6 bit multiplication can be
employed instead of 9 bit multiplication.
[0164] In another (second) example, the grouping is performed in
the same manner as illustrated in FIG. 7, and also the first set S1
is the same as in the first example.
[0165] However, in this example, the set S2 is defined as S2=[-15,
. . . , 15]*2.sup.N, where N is an integer greater than 0. In other
words, the set S2 includes only integer values that can be divided
by 2.sup.N. Moreover, the maximum absolute value has been
restricted to 15*2.sup.N. For instance, if N=1, set S2 does not
include odd valued numbers. In case of N=2, S2=[-30, -28, . . . ,
28,30].
[0166] In this example, the benefit is that for the set S2 4 bit
multiplication can be employed instead of 9 bit multiplication.
[0167] Whereas the first example above provides a pure range
restriction for the coefficients of set S2 as compared to set S1,
the restriction in the foregoing second example can be called a
"granularity and range restriction".
[0168] In still another example within the overall configuration of
FIG. 7, the set S2 is defined as
S2=[-32,-16,-8,-4,-2,-1,0,1,2,4,8,16,32]. Accordingly, the allowed
values in the set S2 are restricted to those that can be
represented with a single "1" in the binary representation with the
maximum absolute allowed value being restricted to 32, i.e. it is
further assumed that the number L is restricted to L=6.
[0169] In this example, the benefit is that instead of 9 bit
multiplication, 1 bit shifting is employed for the set S2.
[0170] Generally, it is noted that the number L (size restriction)
can be set separately and differently for each group. Moreover, the
particular grouping and definition of the sets of the allowed
values can change from image to image (frame to frame).
Alternatively, the grouping and the definition of the sets might be
different for the different filter shapes (e.g., 5.times.5 diamond,
7.times.7 diamond, 9.times.9 diamond as described in FIG. 5).
Alternatively, the grouping and definitions might be
predefined.
[0171] Respective data must be included in the bit stream at the
encoder and signalled to the decoder so that the filter
coefficients can be correctly determined at the decoder as well. Of
course, applying a restricted set of allowed coefficient values
leads to a reduction of the signaling overhead and thus to a more
efficient coding since less bits are necessary for representing the
coefficients to be signaled in the bit stream.
[0172] More specifically, the value of the filter coefficients that
are applied by the encoder needs to be coded and transmitted to the
decoder. On the encoder side, the values of the filter coefficients
are converted into binary codewords (from filter value to codeword)
via a mapping table or a mapping function. The same mapping
operation must be applied in the decoder (from codeword to filter
coefficient value) in order to interpret the filter coefficients
correctly.
[0173] The mapping function or table might be different for S1 and
S2. Example mapping operations are given below for the filter
coefficient sets S1 and S2.
[0174] In the example below S1 is given by {0,1, . . . , 511} and
S2 is given by {0,2,4,8,16,32} (the absolute values are considered
here only).
TABLE-US-00002 S1 S2 Filter coefficient Filter coefficient value
codeword value codeword 0 000000000 0 000 1 000000001 2 001 2
000000010 4 010 3 000000011 8 011 4 000000100 16 100 5 000000101 32
101 6 000000110 . . . 511 111111111
[0175] The forward (in the encoder) and backward (in the decoder)
mapping operations need to be employed in the encoder and decoder
so that the decoder can correctly interpret the filter coefficient
values. In the above example, the filter coefficient mapping
operation is different for S2 and S1, since the number of distinct
values in S2 is much lower and it is wasteful to represent the S2
filter coefficients using the mapping of S1.
[0176] In the following, a general overview of the signaling of
filter coefficients will be given with reference to FIG. 8. FIG. 8
A illustrates the processing on the encoder side and FIG. 8B
illustrates the processing on the decoder side.
[0177] In the encoder, the filter coefficients to be applied on the
reconstructed samples are determined according to the allowed
coefficient values as determined by the particular approach of the
present disclosure (step S80).
[0178] The determined filter coefficients are used to filter the
reconstructed image samples (step S82). According to the present
disclosure, the filter coefficients that are applied on the
reconstructed image samples need to obey the rules as set forth
according to the present disclosure.
[0179] The following step of prediction of filter coefficients
(step S84) is optional. Filter coefficient prediction can be
applied optionally in order to reduce the information to be
signaled to the decoder. Possible prediction methods are prediction
using predefined filter predictors and prediction from previously
signaled filter coefficients. However, the prediction methods are
not limited to these given here by example, and any suitable
prediction method a skilled person is aware of can be applied.
[0180] In the following step (S86) a mapping of the residual
coefficients to binary codewords is performed. Since the foregoing
prediction step S84 is optional, it is noted that alternatively the
mapping is applied directly to the filter coefficients determined
in step S80.
[0181] More specifically, each integer valued filter coefficient
(filter coefficient residual) is converted to a binary codeword
before being included into the bit stream. There are as many
codewords as possible filter coefficient values (filter coefficient
residual values). The codeword to value mapping (which is a
one-to-one mapping) can be a fixed mapping or can change depending
on signaled side information.
[0182] In final step S88, the binarized (optionally residual)
filter coefficients, i.e. the codewords to which they were mapped,
are included in the bit stream. In case prediction is performed in
step S84, it is further necessary to generate a prediction control
information and to include the prediction control information in
the bit stream, in order to signal the decoder the necessary
information about the prediction processing, so as to be able to
perform the reconstruction.
[0183] Generally, the operations applied in the encoder are applied
in the decoder in reverse order. This will be explained in more
detail below with reference to FIG. 8B.
[0184] In initial step S90, a received bit stream is parsed. The
resulting binarized filter coefficients (i.e. transmitted
codewords) are optionally representing residual filter coefficients
(if prediction was applied at the encoder side). This is indicated
by additionally obtaining prediction control information from the
parsed bit stream.
[0185] In any case, the binary codewords are mapped by an inverse
mapping procedure (as compared to the encoder) to the filter
coefficients (or residual filter coefficients) in step S92.
[0186] As a result, the filter coefficients are determined
(reconstructed) on the decoder side (step S94). If prediction was
applied, so that the filter coefficients resulting from step S92
are residual filter coefficients, the reconstruction additionally
includes performing the prediction as indicated by the prediction
control information and adding the prediction result to the
residual filter coefficients, in order to obtain the reconstructed
filter coefficients.
[0187] After the filter coefficients are reconstructed (if
applicable, by combining the predictor information and filter
residuals), they are applied on the reconstructed image samples
(step S96).
[0188] According to the present disclosure, the filter coefficients
that are applied on the reconstructed image samples need to obey
the rules defined according to the present disclosure.
[0189] Accordingly, if a filter coefficient resulting from the
reconstruction (in particular: from combining prediction and
residual results) does not have an allowed filter coefficient value
according to the rules of the present disclosure (a filter
coefficient value that is not among the set of allowed values), the
reconstruction process of filter coefficients further performs a
rounding operation. Specifically, the rounding operation may
convert the input filter coefficient value to the nearest allowed
coefficient value.
[0190] If the filter coefficient prediction is applied, the filter
coefficients to be applied on the reconstructed image samples for
the purpose of filtering are obtained by adding the prediction
result ("predictor") and the residual filter coefficients (as
explained in the previous paragraphs from the encoder and decoder
perspectives). Obviously it is possible that the residual filter
coefficients might be non-existing (equal to 0) especially if the
prediction is close to perfect (the filter coefficients to be
predicted are very similar to the predictor). In this case
according to the present disclosure one of the following 2 options
apply:
[0191] 1. The coefficient values obtained by prediction need to
obey the rules defined according to the present disclosure. For
example in the case of prediction from predefined filters, the
filter coefficients of predefined filters need to obey the rules
defined according to the present disclosure.
[0192] 2. The filter coefficients that are obtained after
prediction need to be rounded to the nearest allowed coefficient
value.
[0193] It is further noted that the division into a number of two
groups has been explained here just for simplicity, but more than
two groups are also possible.
[0194] For instance, FIG. 9 illustrates a case, wherein the
coefficients of the filter are grouped into three groups.
[0195] A first group of coefficients positioned close to the center
of the filter kernel and indicated by filled circles has allowed
filter coefficient values in the set S1=[-511, . . . , 511].
[0196] A second group of filter coefficients, located at the
periphery of the kernel and indicated by broken circles, allows the
filter coefficient values to be within a restricted set S2, wherein
S2 here is S2=[-31,-30,-29, . . . , 0, . . . , 29,30,31]. This is
the set of all coefficient values that can be represented with L=5
binary digits (instead of L=9 in case of S1).
[0197] A third group of filter coefficients, located in-between the
first and the second groups, and indicated by open circles, allows
the filter coefficient values to be within another restricted set
S3, wherein
[0198] S3=[-15,-14,-13, . . . , 13,14,15]*4.
[0199] In other words, the set S3 is the set of all coefficient
values having absolute values below or equal to 60 that are
divisible by 4. These coefficient values can be represented with
L=3 binary digits.
[0200] Another case, wherein the coefficient of the filter are
grouped into three groups, is illustrated in FIG. 10.
[0201] A first group of coefficients positioned close to the center
of the filter kernel has allowed filter coefficient values in the
set S1=[-511, . . . , 511], same as in the previous examples.
[0202] A second group of filter coefficients, located at the
periphery of the kernel and indicated by broken circles, allows the
filter coefficient values to be within a modified restricted set
S2, wherein S2 here is
S2=[-128,-64,-32,-16,-8,-4,-2,-1,0,1,2,4,8,16,32,64,128]. This is
the set of all coefficient values that can be represented with L=8
binary digits, with only a single "one".
[0203] A third group of filter coefficients, located in-between the
first and the second groups, and indicated by filled circles,
allows the filter coefficient values to be within another
restricted set S3, wherein
[0204] S3=[-64,-48,-40, . . . ,
0,1,2,3,4,5,6,8,9,10,12,16,17,18,20,24,32,33,34,36,40,48,64].
[0205] In other words, the set S3 is the set of all coefficients
that can be represented with L=7 binary digits, wherein at most two
of the bits are "one" in the absolute value of the coefficient, and
the additional restriction is applied that the maximum absolute
value is set to 64. (Otherwise, for instance, also the absolute
value 96 should be allowed, since it can be expressed with two
leading "ones" in 7 binary digits.)
[0206] In the following, the particular benefit of the present
disclosure will be described by means of another exemplary
embodiment illustrated in FIG. 11.
[0207] In the example of FIG. 11, the grouping is performed in the
same manner as in FIG. 7.
[0208] The filter coefficients in the first group can assume any
values with nine bits full range and a sign bit, i.e. the
above-mentioned set S1=[-511, 511].
[0209] The filter coefficients in the second group may assume a
restricted set of values S2, wherein S2 here is S2=[-63, . . . ,
63]. This corresponds to those values that can be represented with
L=6 bits and a sign bit.
[0210] In other words, the filter size corresponds to that which
was shown in FIG. 4, i.e. a 9.times.9 diamond shaped filter. As was
indicated in the background section, conventionally 41
multiplications with 9-bit filter coefficients are required. Since
one multiplication is equivalent to 8 binary additions, as
mentioned in the background section, the number of additional
operations per pixel is 48*8=328 addition operations.
[0211] According to the present disclosure, there are 13
multiplication operations with 9-bit coefficients and 28
multiplications with 6-bit coefficients. This adds up to
(28*8+13*5)=289 additions. The number of operations per pixel is
thus reduced by 10%.
[0212] The numbers above are rough estimations and the exact value
of reduction in complexity depends on the actual implementation.
Namely in the above calculations, the complexity of bit-shifting
operation is assumed to be negligible, and moreover the complexity
of the multiplication of 2 M-bit numbers is assumed to be
equivalent to M-1 addition operations. This implementation
complexity approximation would be considered good and sufficient
for most hardware implementations.
[0213] According to the present disclosure, not all of the filter
coefficients are coarsely quantized, and the filter coefficients in
the first group have finer quantization.
[0214] Normally, coarse quantization of filter coefficients causes
the coding loss. However, having the first group of filter
coefficients allowed to assume a large set of values can be used to
compensate for the coding loss by the encoder.
[0215] A possible encoder implementation is as follows. In the
following description, the filter coefficient labels used are those
as indicated in FIG. 12, which may differ from the labels
previously used in connection with other drawings:
[0216] Step 1: Derive all of the filter coefficients (C.sub.0, . .
. C.sub.20) using the least squares method by assuming no
restriction on the coefficient values.
[0217] Step 2: Impose the restriction by rounding the coefficients
(C.sub.7, . . . , C.sub.20) to the closest allowed value.
[0218] This step introduces quantization noise in filter
coefficients and thus reduces the coding gain.
[0219] Step 3: Re-estimate the freely selectable filter
coefficients (C.sub.0, . . . , C.sub.6) in order to compensate for
the quantization errors. In this third step, most of the coding
loss that is introduced in step 2 can be recovered.
[0220] In more detail:
[0221] In the first step, the equation given below is solved for
the 41 tap filter (with 21 unique coefficients):
[ X 0 , 0 X 0 , 1 X 0 , 20 X 19 , 0 X 19 , 1 X 19 , 20 X 20 , 0 X
20 , 1 X 20 , 20 ] [ C 0 C 19 C 20 ] = [ P 0 P 19 P 20 ]
##EQU00004##
[0222] The equation above is called the least squares equation and
is used to find the filter coefficients C.sub.x in the encoder.
[0223] The X.sub.x,y term is the expected value of
R(i+k,j+l)*R(i+m,j+n), the correlation between the 2 reconstructed
samples before filtering. The indices k, l, m and n are selected
according to the shape of the filter to be applied.
[0224] The term P.sub.x denotes the expected value of
R(i+k,j+l)*O(i,j).
[0225] In the second step, for filter coefficients C.sub.7 to
C.sub.20, the closest approximate coefficients are found that
satisfy the restrictions:
f ( [ C 7 C 19 C 20 ] ) = [ C 7 ' C 19 ' C 20 ' ] ##EQU00005##
[0226] The coefficients C.sub.7' to C.sub.20' obey the rules
specified by the present disclosure. Please note that the function
f( ) described above introduces quantization noise to the filter
coefficients C.sub.7 to C.sub.20 that were previously obtained by
solving the least squares equation.
[0227] The quantization noise introduced in the second step is
expected to reduce the performance of filtering operation. The
performance of filtering is usually measured by a metric such as
PSNR (Peak signal-to-noise ratio), hence after step 2, the PSNR of
the filtered image will be reduced.
[0228] In the third step, the equation below is solved for a 13 tap
filter (with 7 unique coefficients):
[ X 0 , 0 X 0 , 1 X 0 , 6 X 5 , 0 X 5 , 1 X 5 , 6 X 6 , 0 X 6 , 1 X
5 , 5 ] [ C 0 C 5 C 6 ] = [ P 0 - C 7 ' * X 0 , 7 - - C 20 ' * X 0
, 20 P 5 - C 7 ' * X 5 , 7 - - C 20 ' * X 5 , 20 P 6 - C 7 ' * X 6
, 7 - - C 20 ' * X 6 , 20 ] ##EQU00006##
[0229] In the third step the filtering coefficients C.sub.0 to
C.sub.7 are computed again taking into account the quantization
noise introduced in the second step. The third step advantageously
reduces the reduction in filtering performance that is caused by
application of step 2.
[0230] It is noted that in general the application of filtering
operation with adaptive multiplicative filter coefficients is not
limited to reconstructed image samples. As described in FIGS. 2 and
3, the reconstructed block usually corresponds to the image block
that is obtained after the combination of inverse transformed block
and prediction block. As it is apparent to the person skilled in
art, the filtering operation with adaptive filter coefficients can
also be applied at the other steps of the encoding and decoding
operations, e.g., to prediction block (265, 165), inverse
transformed block (213, 113) quantized coefficients (209, 109),
de-quantized coefficients (111, 211) or decoded picture (231). In
this case the present disclosure applies to the filter coefficients
of filtering operation.
[0231] In summary, the present disclosure relates to an improved
apparatus and method for filtering reconstructed images, in
particular, video images, with adaptive multiplicative filters. The
efficiency of the filtering operation is increased by grouping the
filter coefficients in at least two groups and restricting the
allowable values of the filter coefficients for one group as
compared to the other group.
[0232] Note that this specification provides explanations for
pictures (frames), but fields substitute as pictures in the case of
an interlace picture signal.
[0233] Although embodiments of the present disclosure have been
primarily described based on video coding, it should be noted that
embodiments of the encoder 100 and decoder 200 (and correspondingly
the system 300) may also be configured for still picture processing
or coding, i.e. the processing or coding of an individual picture
independent of any preceding or consecutive picture as in video
coding. In general only inter-estimation 142, inter-prediction 144,
242 are not available in case the picture processing coding is
limited to a single picture 101. Most if not all other
functionalities (also referred to as tools or technologies) of the
video encoder 100 and video decoder 200 may equally be used for
still pictures, e.g., partitioning, transformation (scaling) 106,
quantization 108, inverse quantization 110, inverse transformation
112, intra-estimation 142, intra-prediction 154, 254 and/or loop
filtering 120, 220, and entropy coding 170 and entropy decoding
204.
[0234] Wherever embodiments and the description refer to the term
"memory", the term "memory" shall be understood and/or shall
comprise a magnetic disk, an optical disc, a solid state drive
(SSD), a read-only memory (Read-Only Memory, ROM), a random access
memory (Random Access Memory, RAM), a USB flash drive, or any other
suitable kind of memory, unless explicitly stated otherwise.
[0235] Wherever embodiments and the description refer to the term
"network", the term "network" shall be understood and/or shall
comprise any kind of wireless or wired network, such as Local Area
Network (LAN), Wireless LAN (WLAN) Wide Area Network (WAN), an
Ethernet, the Internet, mobile networks etc., unless explicitly
stated otherwise.
[0236] The person skilled in the art will understand that the
"blocks" ("units" or "modules") of the various figures (method and
apparatus) represent or describe functionalities of embodiments of
the present disclosure (rather than necessarily individual "units"
in hardware or software) and thus describe equally functions or
features of apparatus embodiments as well as method embodiments
(unit=step).
[0237] The terminology of "units" is merely used for illustrative
purposes of the functionality of embodiments of the encoder/decoder
and are not intended to limit the disclosure.
[0238] In the several embodiments provided in the present
application, it should be understood that the disclosed system,
apparatus, and method may be implemented in other manners. For
example, the described apparatus embodiment is merely exemplary.
For example, the unit division is merely logical function division
and may be another division in an actual implementation. For
example, a plurality of units or components may be combined or
integrated into another system, or some features may be ignored or
not performed. In addition, the displayed or discussed mutual
couplings or direct couplings or communication connections may be
implemented by using some interfaces. The indirect couplings or
communication connections between the apparatuses or units may be
implemented in electronic, mechanical, or other forms.
[0239] The units described as separate parts may or may not be
physically separate, and parts displayed as units may or may not be
physical units, may be located in one position, or may be
distributed on a plurality of network units. Some or all of the
units may be selected according to actual needs to achieve the
objectives of the solutions of the embodiments.
[0240] In addition, functional units in the embodiments of the
present disclosure may be integrated into one processing unit, or
each of the units may exist alone physically, or two or more units
are integrated into one unit.
[0241] Embodiments of the present disclosure may further comprise
an apparatus, e.g., encoder and/or decoder, which comprises a
processing circuitry configured to perform any of the methods
and/or processes described herein.
[0242] Embodiments of the encoder 100 and/or decoder 200 may be
implemented as hardware, firmware, software or any combination
thereof. For example, the functionality of the encoder/encoding or
decoder/decoding may be performed by a processing circuitry with or
without firmware or software, e.g., a processor, a microcontroller,
a digital signal processor (DSP), a field programmable gate array
(FPGA), an application-specific integrated circuit (ASIC), or the
like.
[0243] The functionality of the encoder 100 (and corresponding
encoding method 100) and/or decoder 200 (and corresponding decoding
method 200) may be implemented by program instructions stored on a
computer readable medium. The program instructions, when executed,
cause a processing circuitry, computer, processor or the like, to
perform the steps of the encoding and/or decoding methods. The
computer readable medium can be any medium, including
non-transitory storage media, on which the program is stored such
as a Blu ray disc, DVD, CD, USB (flash) drive, hard disc, server
storage available via a network, etc.
[0244] An embodiment of the present disclosure comprises or is a
computer program comprising program code for performing any of the
methods described herein, when executed on a computer.
[0245] An embodiment of the present disclosure comprises or is a
computer readable medium comprising a program code that, when
executed by a processor, causes a computer system to perform any of
the methods described herein.
[0246] An embodiment of the present disclosure comprises or is a
chipset performing any of the methods described herein.
LIST OF REFERENCE SIGNS
[0247] 100 Encoder
[0248] 102 Input (e.g., input port, input interface)
[0249] 103 Picture block
[0250] 104 Residual calculation [unit or step]
[0251] 105 Residual block
[0252] 106 Transformation (e.g., additionally comprising scaling)
[unit or step]
[0253] 107 Transformed coefficients
[0254] 108 Quantization [unit or step]
[0255] 109 Quantized coefficients
[0256] 110 Inverse quantization [unit or step]
[0257] 111 De-quantized coefficients
[0258] 112 Inverse transformation (e.g., additionally comprising
scaling) [unit or step]
[0259] 113 Inverse transformed block
[0260] 114 Reconstruction [unit or step]
[0261] 115 Reconstructed block
[0262] 116 (Line) buffer [unit or step]
[0263] 117 Reference samples
[0264] 120 Loop filter [unit or step]
[0265] 121 Filtered block
[0266] 130 Decoded picture buffer (DPB) [unit or step]
[0267] 142 Inter estimation (or inter picture estimation) [unit or
step]
[0268] 143 Inter estimation parameters (e.g., reference
picture/reference picture index, motion vector/offset)
[0269] 144 Inter prediction (or inter picture prediction) [unit or
step]
[0270] 145 Inter prediction block
[0271] 152 Intra estimation (or intra picture estimation) [unit or
step]
[0272] 153 Intra prediction parameters (e.g., intra prediction
mode)
[0273] 154 Intra prediction (intra frame/picture prediction) [unit
or step]
[0274] 155 Intra prediction block
[0275] 162 Mode selection [unit or step]
[0276] 165 Prediction block (either inter prediction block 145 or
intra prediction block 155)
[0277] 170 Entropy encoding [unit or step]
[0278] 171 Encoded picture data (e.g., bitstream)
[0279] 172 Output (output port, output interface)
[0280] 200 Decoder
[0281] 202 Input (port/interface)
[0282] 204 Entropy decoding
[0283] 209 Quantized coefficients
[0284] 210 Inverse quantization
[0285] 211 De-quantized coefficients
[0286] 212 Inverse transformation (scaling)
[0287] 213 Inverse transformed block
[0288] 214 Reconstruction (unit)
[0289] 215 Reconstructed block
[0290] 216 (Line) buffer
[0291] 217 Reference samples
[0292] 220 Loop filter (in loop filter)
[0293] 221 Filtered block
[0294] 230 Decoded picture buffer (DPB)
[0295] 231 Decoded picture
[0296] 232 Output (port/interface)
[0297] 244 Inter prediction (inter frame/picture prediction)
[0298] 245 Inter prediction block
[0299] 254 Intra prediction (intra frame/picture prediction)
[0300] 255 Intra prediction block
[0301] 260 Mode selection
[0302] 265 Prediction block (inter prediction block 245 or intra
prediction block 255)
[0303] 300 Coding system
[0304] 310 Source device
[0305] 312 Picture Source
[0306] 313 (Raw) picture data
[0307] 314 Pre-processor/Pre-processing unit
[0308] 315 Pre-processed picture data
[0309] 318 Communication unit/interface
[0310] 320 Destination device
[0311] 322 Communication unit/interface
[0312] 326 Post-processor/Post-processing unit
[0313] 327 Post-processed picture data
[0314] 328 Display device/unit
[0315] 330 transmitted/received/communicated (encoded) picture
data
* * * * *